25,953 research outputs found

    A Firewall Optimization for Threat-Resilient Micro-Segmentation in Power System Networks

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    Electric power delivery relies on a communications backbone that must be secure. SCADA systems are essential to critical grid functions and include industrial control systems (ICS) protocols such as the Distributed Network Protocol-3 (DNP3). These protocols are vulnerable to cyber threats that power systems, as cyber-physical critical infrastructure, must be protected against. For this reason, the NERC Critical Infrastructure Protection standard CIP-005-5 specifies that an electronic system perimeter is needed, accomplished with firewalls. This paper presents how these electronic system perimeters can be optimally found and generated using a proposed meta-heuristic approach for optimal security zone formation for large-scale power systems. Then, to implement the optimal firewall rules in a large scale power system model, this work presents a prototype software tool that takes the optimization results and auto-configures the firewall nodes for different utilities in a cyber-physical testbed. Using this tool, firewall policies are configured for all the utilities and their substations within a synthetic 2000-bus model, assuming two different network topologies. Results generate the optimal electronic security perimeters to protect a power system's data flows and compare the number of firewalls, monetary cost, and risk alerts from path analysis.Comment: 12 pages, 22 figure

    AI-Generated Incentive Mechanism and Full-Duplex Semantic Communications for Information Sharing

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    The next generation of Internet services, such as Metaverse, rely on mixed reality (MR) technology to provide immersive user experiences. However, the limited computation power of MR headset-mounted devices (HMDs) hinders the deployment of such services. Therefore, we propose an efficient information sharing scheme based on full-duplex device-to-device (D2D) semantic communications to address this issue. Our approach enables users to avoid heavy and repetitive computational tasks, such as artificial intelligence-generated content (AIGC) in the view images of all MR users. Specifically, a user can transmit the generated content and semantic information extracted from their view image to nearby users, who can then use this information to obtain the spatial matching of computation results under their view images. We analyze the performance of full-duplex D2D communications, including the achievable rate and bit error probability, by using generalized small-scale fading models. To facilitate semantic information sharing among users, we design a contract theoretic AI-generated incentive mechanism. The proposed diffusion model generates the optimal contract design, outperforming two deep reinforcement learning algorithms, i.e., proximal policy optimization and soft actor-critic algorithms. Our numerical analysis experiment proves the effectiveness of our proposed methods. The code for this paper is available at https://github.com/HongyangDu/SemSharingComment: Accepted by IEEE JSA

    Challenges in the Design and Implementation of IoT Testbeds in Smart-Cities : A Systematic Review

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    Advancements in wireless communication and the increased accessibility to low-cost sensing and data processing IoT technologies have increased the research and development of urban monitoring systems. Most smart city research projects rely on deploying proprietary IoT testbeds for indoor and outdoor data collection. Such testbeds typically rely on a three-tier architecture composed of the Endpoint, the Edge, and the Cloud. Managing the system's operation whilst considering the security and privacy challenges that emerge, such as data privacy controls, network security, and security updates on the devices, is challenging. This work presents a systematic study of the challenges of developing, deploying and managing urban monitoring testbeds, as experienced in a series of urban monitoring research projects, followed by an analysis of the relevant literature. By identifying the challenges in the various projects and organising them under the V-model development lifecycle levels, we provide a reference guide for future projects. Understanding the challenges early on will facilitate current and future smart-cities IoT research projects to reduce implementation time and deliver secure and resilient testbeds

    Secure Short-Packet Communications via UAV-Enabled Mobile Relaying: Joint Resource Optimization and 3D Trajectory Design

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    Short-packet communication (SPC) and unmanned aerial vehicles (UAVs) are anticipated to play crucial roles in the development of 5G-and-beyond wireless networks and the Internet of Things (IoT). In this paper, we propose a secure SPC system, where a UAV serves as a mobile decode-and-forward (DF) relay, periodically receiving and relaying small data packets from a remote IoT device to its receiver in two hops with strict latency requirements, in the presence of an eavesdropper. This system requires careful optimization of important design parameters, such as the coding blocklengths of both hops, transmit powers, and UAV's trajectory. While the overall optimization problem is nonconvex, we tackle it by applying a block successive convex approximation (BSCA) approach to divide the original problem into three subproblems and solve them separately. Then, an overall iterative algorithm is proposed to obtain the final design with guaranteed convergence. Our proposed low-complexity algorithm incorporates 3D trajectory design and resource management to optimize the effective average secrecy throughput of the communication system over the course of UAV-relay's mission. Simulation results demonstrate significant performance improvements compared to various benchmark schemes and provide useful design insights on the coding blocklengths and transmit powers along the trajectory of the UAV

    Guest editorial: special issue on recent advances in security and privacy for 6G networks

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    Outage analysis of millimeter wave RSMA systems

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    Millimeter-wave (mmWave) communication has attracted considerable attention from academia and industry, providing multi-gigabits per second rates due to the substantial bandwidth. Rate splitting multiple access (RSMA) is an effective technology that provides a generalized multiple access framework. Regarding the new propagation characteristics of the mmWave, we investigate the outage performance of the mmWave RSMA multiple-input-single-output system with a fixed-located user and a randomly-located user. Based on the spatial correlation of the paired users, the user’s paths are divided into overlapped and non-overlapped paths. Two beamforming schemes are proposed to improve the reliability of the mmWave RSMA system. The common stream is transmitted on the overlapped paths or all the paths. By utilizing stochastic geometry theory, the closed-form expressions of the outage probability (OP) with proposed schemes are derived. To obtain more insights, the expressions for the asymptotic OP are derived. Monte Carlo simulation results are presented to validate the analysis and the effects of the system parameters, such as power allocation coefficients and the number of resolvable paths, on the outage performance are investigated

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    Unmanned-Aircraft-System-Assisted Early Wildfire Detection with Air Quality Sensors †

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    Numerous Hectares of Land Are Destroyed by Wildfires Every Year, Causing Harm to the Environment, the Economy, and the Ecology. More Than Fifty Million Acres Have Burned in Several States as a Result of Recent Forest Fires in the Western United States and Australia. According to Scientific Predictions, as the Climate Warms and Dries, Wildfires Will Become More Intense and Frequent, as Well as More Dangerous. These Unavoidable Catastrophes Emphasize How Important Early Wildfire Detection and Prevention Are. the Energy Management System Described in This Paper Uses an Unmanned Aircraft System (UAS) with Air Quality Sensors (AQSs) to Monitor Spot Fires Before They Spread. the Goal Was to Develop an Efficient Autonomous Patrolling System that Detects Early Wildfires While Maximizing the Battery Life of the UAS to Cover Broad Areas. the UAS Will Send Real-Time Data (Sensor Readings, Thermal Imaging, Etc.) to a Nearby Base Station (BS) When a Wildfire is Discovered. an Optimization Model Was Developed to Minimize the Total Amount of Energy Used by the UAS While Maintaining the Required Levels of Data Quality. Finally, the Simulations Showed the Performance of the Proposed Solution under Different Stability Conditions and for Different Minimum Data Rate Types

    Bayesian Forecasting in Economics and Finance: A Modern Review

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    The Bayesian statistical paradigm provides a principled and coherent approach to probabilistic forecasting. Uncertainty about all unknowns that characterize any forecasting problem -- model, parameters, latent states -- is able to be quantified explicitly, and factored into the forecast distribution via the process of integration or averaging. Allied with the elegance of the method, Bayesian forecasting is now underpinned by the burgeoning field of Bayesian computation, which enables Bayesian forecasts to be produced for virtually any problem, no matter how large, or complex. The current state of play in Bayesian forecasting in economics and finance is the subject of this review. The aim is to provide the reader with an overview of modern approaches to the field, set in some historical context; and with sufficient computational detail given to assist the reader with implementation.Comment: The paper is now published online at: https://doi.org/10.1016/j.ijforecast.2023.05.00

    A Survey on 5G Coverage Improvement Techniques: Issues and Future Challenges

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    Fifth generation (5G) is a recent wireless communication technology in mobile networks. The key parameters of 5G are enhanced coverage, ultra reliable low latency, high data rates, massive connectivity and better support to mobility. Enhanced coverage is one of the major issues in the 5G and beyond 5G networks, which will be affecting the overall system performance and end user experience. The increasing number of base stations may increase the coverage but it leads to interference between the cell edge users, which in turn impacts the coverage. Therefore, enhanced coverage is one of the future challenging issues in cellular networks. In this survey, coverage enhancement techniques are explored to improve the overall system performance, throughput, coverage capacity, spectral efficiency, outage probability, data rates, and latency. The main aim of this article is to highlight the recent developments and deployments made towards the enhanced network coverage and to discuss its future research challenges
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